We implemented a batch closure utility for obsolete ECOs that significantly improved our change management workflow and reporting accuracy. Our dashboard showed 847 open ECOs, but manual audit revealed 412 were actually completed months ago and never formally closed. This created misleading metrics for management and complicated change tracking.
The solution involved developing a batch utility using ECO Batch Utility framework in TC 13.1 that:
- Queries ECOs with implemented status older than 90 days
- Generates pre-closure validation report checking for open tasks, pending approvals
- Executes batch closure with proper state transitions
- Updates dashboard metrics in real-time
Implementation took 3 weeks including testing. Now runs weekly via scheduled task, processing 50-80 ECOs per cycle. Dashboard accuracy improved from 51% to 97%, and change managers have cleaner reporting for executive reviews.
We initially had the same 24-hour lag issue with OOTB dashboard updates. Solution was implementing a post-batch service that directly updates the analytics cache tables. After the batch closure completes, we trigger a targeted refresh of affected metrics rather than waiting for the scheduled full recalc. This reduced update lag from 24 hours to under 5 minutes. The key was identifying which specific cache tables needed immediate refresh versus letting others update on normal schedule.
This is exactly what we need! Our ECO backlog is a mess with hundreds showing open when they’re actually done. Quick question - how do you handle ECOs that have implemented parts but still have open documentation tasks? Do you close them anyway or skip them in the batch run?
Valid concern. We maintained upgrade compatibility by using only documented APIs from the ECO Batch Utility framework rather than direct database manipulation. Before our TC 13.1 to 13.3 upgrade, we ran the utility in test environment for 2 weeks processing historical data. Only change needed was updating one deprecated method call. The pre-closure validation report is especially valuable during upgrades - helps identify any configuration drift or custom workflow changes that might affect batch processing logic.
Interesting approach. We built something similar but struggled with the dashboard metric updates. Are you using the standard ECO lifecycle state change events to trigger metric recalculation, or did you implement a custom refresh mechanism? We found the OOTB dashboard sometimes took 24+ hours to reflect batch closures, which defeated the purpose of real-time visibility. Ended up writing a custom service to force immediate dashboard refresh after each batch completion. Would be curious to know your technical approach on that specific aspect.